README.md

MADS (Model Analysis & Decision Support)

MADS is an integrated open-source high-performance computational (HPC) framework in Julia.
MADS can execute a wide range of data- and model-based analyses:

Sensitivity Analysis

Parameter Estimation

Model Inversion and Calibration

Uncertainty Quantification

Model Selection and Model Averaging

Model Reduction and Surrogate Modeling

Machine Learning and Blind Source Separation

Decision Analysis and Support

MADS has been tested to perform HPC simulations on a wide-range multi-processor clusters and parallel environments (Moab, Slurm, etc.).
MADS utilizes adaptive rules and techniques which allows the analyses to be performed with a minimum user input.
The code provides a series of alternative algorithms to execute each type of data- and model-based analyses.